25 Crown Jewels

Stops your LLM from making things up and from being hijacked by malicious prompts. Grounds answers in source-of-truth, sanitizes inputs, clamps outputs, and scores response quality before it reaches the user.

Front-door protection: throttles abusive callers, blocks unknown origins, signature-checks payloads, and redacts API keys or secrets before they ever leave a log line.

Automatically finds and masks personal data (emails, phone numbers, IDs, sensitive keys) in every request, response, and log — so a single mistake can't leak a customer's identity.

Models who-can-call-what as a trust graph, detects suspicious call cycles, and refuses any execution path that crosses a forbidden boundary — stops privilege-escalation chains before they execute.

Plants invisible canary tokens to catch attackers in the act, classifies them by behavior, and permanently blocks repeat offenders — turns probes into actionable threat intel.

Drop-in production telemetry: live counters, latency histograms, drift sensors, and an anomaly verdict — see what's slow, broken, or off-baseline without bolting on a separate metrics stack.

Continuously checks every call against GDPR, HIPAA, PCI, and SOC2 rules, keeps a permanent finding trail, and produces rolling-window certification you can hand to an auditor.

Builds a behavioral fingerprint of every capability, watches for drift from that baseline, and quarantines anything that suddenly behaves differently — catches silent regressions and supply-chain tampering.

Six weighted ethical axes that score every input and output, then allow, sieve, or embargo the action — gives your AI a conscience without hand-coding rules.

Fingerprints every fault, escalates by recurrence (observed → repeating → recurring), and tells the always-on Hardening Layer to quarantine repeat offenders — so the same bug never bites you twice.

Seals every capability call as a deterministic replay capsule. Reproduce any production bug locally — exact inputs, exact seeds, exact result — without staging data or guesswork.

Watches your live metrics, smooths the noise, and automatically retunes thresholds or triggers a clean re-genesis when conditions breach — no more manually chasing config knobs at 3am.

Generates structured outputs from templates with slot validation, schema inference from samples, and a safety check on every result — production-safe alternative to free-form LLM generation.

Queues code or config patches, simulates dependencies in topological order, and refuses to ship any sequence that would break something downstream — safe deploys without a release engineer.

Wire 'when X happens, do Y' across services with conditional triggers, cost calculation, and an append-only firing ledger — replaces a half-dozen ad-hoc webhook scripts with one auditable registry.

Builds a behavioral profile per user (typing cadence, call patterns, timing) and continuously re-verifies them — catches stolen sessions and account takeovers a password check can't.

Sleep-cycle for your runtime: decays weakly-used patterns, reinforces high-utility ones, and surfaces the strongest paths — keeps long-running systems from drowning in stale state.

Validates every payload against a schema contract, merges multi-source inputs, and returns a structured receipt of what matched, what was missing, and what was extra — kills silent integration mismatches.

Watches your traffic, detects which input shapes recur, and automatically promotes them into named, routable gateways — your API self-organizes around real usage instead of guessed-at endpoints.

Learns the shape of your API from real traffic, generates typed I/O contracts you didn't have to write, and alerts when callers drift from them — schema-first hygiene without the upfront cost.

Translates, transcreates, and persona-shifts strings across locales with locale → language → root fallback — ship a multilingual product without juggling a dozen translation files.

Watches access patterns and brokers ledgered, audited contracts between callers and providers — turn ad-hoc 'just call OpenAI' code into enforceable, swappable AI agreements.

Asks N AI models the same question, returns the majority answer plus an agreement score and dissent list — catch hallucinations and edge-case disagreements before they reach the user.

Classifies records by region (EU, US, APAC) and gates cross-region access at the function-call boundary — meet GDPR / data-residency contracts without re-architecting your storage.

Runs an adversarial corpus against every capability on a schedule, reports pass-rate and weakest defender — automated red-teaming so you find the hole before an attacker does.